Development Of Turbulence Research Articles

Modeling Kelvin Helmholtz Instability Tube and Knot Dynamics and Their Impact on Mixing in the Lower Thermosphere

AbstractWe present modeling results of tube and knot (T&K) dynamics accompanying thermospheric Kelvin Helmholtz Instabilities (KHI) in an event captured by the 2018 Super Soaker campaign (R. L. Mesquita et al., 2020, https://doi.org/10.1029/2020JA027972). Chemical tracers released by a rocketsonde on 26 January 2018 showed coherent KHI in the lower thermosphere that rapidly deteriorated within 45–90 s. Using wind and temperature data from the event, we conducted high resolution direct numerical simulations (DNS) employing both wide and narrow spanwise domains to facilitate (wide domain case) and prohibit (narrow domain case) the axial deformation of KH billows that allows tubes and knots to form. KHI T&K dynamics are shown to produce accelerated instability evolution consistent with the observations, achieving peak dissipation rates nearly two times larger and 1.8 buoyancy periods faster than axially uniform KHI generated by the same initial conditions. Rapidly evolving twist waves are revealed to drive the transition to turbulence; their evolution precludes the formation of secondary convective instabilities and secondary KHI seen to dominate the turbulence evolution in artificially constrained laboratory and simulation environments. T&K dynamics extract more kinetic energy from the background environment and yield greater irreversible energy exchange and entropy production, yet they do so with weaker mixing efficiency due to greater energy dissipation. The results suggest that enhanced mixing from thermospheric KHI T&K events could account for the discrepancy between modeled and observed mixing in the lower thermosphere (Garcia et al., 2014, https://doi.org/10.1002/2013JD021208; Liu, 2021, https://doi.org/10.1029/2020GL091474) and merits further study.

Effects of subgrid‐scale turbulence parametrization on the representation of clear‐air turbulence using kilometre‐ to hectometre‐scale numerical simulations

A turbulence event arising in a jet exit region above the Belgium–Luxembourg area, determined from airliner in‐situ measurements, is reproduced using the meteorological models Application de la Recherche à l'Opérationnel à Méso‐Echelle (AROME) and Meso‐NH at horizontal resolutions of 1.3 km and 260 m. The behaviour of the subgrid turbulence scheme at 1.3 km and its sensitivity to various parameters are analysed, with results being evaluated using measurements. An increase of the vertical resolution around the tropopause levels with m is shown to greatly enhance the turbulence representation. The use of a non‐local formulation of the mixing length in the current parametrization at 1.3 km allows reproduction of a turbulence signal in agreement with the observations. On the contrary, the use of a fully three‐dimensional formulation has no impact on the simulation at this resolution (1.3 km). Using the 260 m runs, this turbulence event is linked to hydrodynamical wind shear instabilities characterized by horizontal wavelength of 4.5 km, sub‐resolved at the operational resolution. At these small grid‐size scales, turbulence evolution and equation budgets reflect an equilibrium between dynamical production and turbulence dissipation, and highlight the importance of horizontal gradients. Subgrid turbulence intensities are assessed to be underestimated by the current parametrization at 1.3 km when compared with this high‐resolution reference simulation. Finally, different tests on the turbulence parametrization illustrate a transfer between resolved and subgrid kinetic energy in the model. This transfer stresses the importance of a trade‐off between mixing intensity and the representation of wind at resolved scales for the upper troposphere.

Observations of Kolmogorov Turbulence in Saturn's Magnetosphere

AbstractThe Kolmogorov scaling in the inertial range of scales is a distinct characteristic of fully developed turbulence, and studying it offers valuable insights into the evolution of turbulence. In this work, we perform a statistical survey of the power spectra with the Kolmogorov scaling in Saturn's magnetosphere using Cassini measurements. Two cases study show that both magnetic‐field and electron density spectra exhibit f −5/3 at the MHD scales. The statistical analysis reveals a wide‐ranging and abundant presence of Kolmogorov spectra throughout magnetosphere, observed across all local times. Interestingly, the occurrence rate of these Kolmogorov‐like events within Saturn's magnetosphere surpasses that observed in the planetary magnetosheath. The measurements of magnetic compressibility for the Kolmogorov‐like events show the dominance of incompressible Alfvénic turbulence (44.64%) with respect to magnetosonic‐like one (6.94%). In addition, the source and evolution of the turbulent fluctuations are further discussed.

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

A Three-dimensional Model for the Evolution of Magnetohydrodynamic Turbulence in the Outer Heliosphere

We present a time-dependent, three-dimensional single-fluid model for the transport of magnetohydrodynamic (MHD) turbulence that is self-consistently evolving with a dynamic large-scale solar wind in the outer heliosphere. The emphasis is on the region beyond the termination shock, where the solar wind expands subsonically, as well as sub-Alfvénically and nonradially. In extension of earlier work, we refine the treatment of turbulence by considering, in addition to the Elsässer energies, a nonconstant energy difference (or residual energy) and by allowing each of these quantities its own characteristic correlation length scale. While the nonlinear effects in the equations for the Elsässer energies and their length scales are implemented using familiar von Kármán–Howarth style modeling of homogeneous MHD turbulence, the energy difference, which is not conserved in the absence of dissipation, and its length scale are modeled using distinct approaches. We also clarify the impact of the choice of measurement direction for correlation functions associated with two-dimensional fluctuations in transport models. Finally, we illustrate and study the solutions of the resulting six-equation model in detail.

Nocturnal Turbulence at Jezero Crater as Determined From MEDA Measurements and Modeling

AbstractMars 2020 Mars Environmental Dynamics Analyzer (MEDA) instrument data acquired during half of a Martian year (Ls 13°–180°), and modeling efforts with the Mars Regional Atmospheric Modeling System (MRAMS) and the Mars Climate Database (MCD) enable the study of the seasonal evolution and variability of nocturnal atmospheric turbulence at Jezero crater. Nighttime conditions in Mars's Planetary Boundary Layer are highly stable because of strong radiative cooling that efficiently inhibits convection. However, MEDA nighttime observations of simultaneous rapid fluctuations in horizontal wind speed and air temperatures suggest the development of nighttime turbulence in Jezero crater. Mesoscale modeling with MRAMS also shows a similar pattern and enables us to investigate the origins of this turbulence and the mechanisms at play. As opposed to Gale crater, less evidence of turbulence from breaking mountain wave activity was found in Jezero during the period studied with MRAMS. On the contrary, the model suggests that nighttime turbulence at Jezero crater is explained by increasingly strong wind shear produced by the development of an atmospheric bore‐like disturbance at the nocturnal inversion interface. These atmospheric bores are produced by downslope winds from the west rim undercutting a strong low‐level jet aloft from ∼19:00 to 01:00 LTST and from ∼01:00 LTST to dawn when undercutting weak winds aloft. The enhanced wind shear leads to a reduction in the Richardson number and an onset of mechanical turbulence. Once the critical Richardson Number is reached (Ri ∼ <0.25), shear instabilities can mix warmer air aloft down to the surface.

Multi-Scale Feature Residual Feedback Network for Super-Resolution Reconstruction of the Vertical Structure of the Radar Echo

The vertical structure of radar echo is crucial for understanding complex microphysical processes of clouds and precipitation, and for providing essential data support for the study of low-level wind shear and turbulence formation, evolution, and dissipation. Therefore, finding methods to improve the vertical data resolution of the existing radar network is crucial. Existing algorithms for improving image resolution usually focus on increasing the width and height of images. However, improving the vertical data resolution of weather radar requires a focus on improving the elevation angle resolution while maintaining distance resolution. To address this challenge, we propose a network for super-resolution reconstruction of weather radar echo vertical structures. The network is based on a multi-scale residual feedback network (MR-FBN) and uses new multi-scale feature residual blocks (MSRB) to effectively extract and utilize data features at different scales. The feedback network gradually generates the final high-resolution vertical structure data. In addition, we propose an elevation upsampling layer (EUL) specifically for this task, replacing the traditional image subpixel convolution layer. Experimental results show that the proposed method can effectively improve the elevation angle resolution of weather radar echo vertical structure data, providing valuable help for atmospheric detection.

Effects of Atmospheric Coherent Time on Inverse Synthetic Aperture Ladar Imaging through Atmospheric Turbulence

Inverse synthetic aperture ladar (ISAL) can achieve high-resolution images for long-range moving targets, while its performance is affected by atmospheric turbulence. In this paper, the dynamic evolution of atmospheric turbulence is studied by using an infinitely long phase screen (ILPS), and the atmospheric coherent time is defined to describe the variation speed of the phase fluctuation induced by atmospheric turbulence. The simulation results show that the temporal decoherence of the echo induced by turbulence causes phase fluctuation and introduces an extra random phase, which deteriorates the phase stability and makes coherent synthesis impossible. Thus, we evaluated its effects on ISAL imaging and found a method to mitigate the impact of turbulence on ISAL images. The phase compensation algorithm could correct the phase variation in different pulses instead of that within the same pulse. Therefore, the relationship between the atmospheric coherent time and pulse duration time (rather than that between the atmospheric coherent time and ISAL imaging time) ultimately determines the ISAL imaging quality. Furthermore, these adverse effects could be mitigated by increasing the atmospheric coherent time or decreasing the pulse duration time, which results in an improvement in the ISAL imaging quality.

Direct numerical simulations of cooling flow and heat transfer in supercritical CO2 Brayton cycle coupled with solar energy

Direct numerical simulation was used to study supercritical carbon dioxide’s flow and heat transfer mechanisms under cooling conditions in the supercritical CO2 Brayton Cycle coupled with solar energy. This paper aims to investigate the effects of property variation, buoyancy, and thermal deceleration under different flow conditions. Momentum balance analysis is used to quantify changes caused by different mechanisms and to describe the flow and turbulence evolution characteristics. In forced convection, due to the dominant thermal deceleration effect, the pressure gradient decreases across the entire cross-section, resulting in the deceleration of the fluid. In upward flow, buoyancy plays a dominant role and acts as a resistance, causing the pressure gradient to increase significantly. As a result, when the core fluid accelerates, the velocity of the near-wall fluid slows significantly, enhancing heat transfer, and the Nusselt number increases by up to 33.21% compared to forced convection. In downward flow, buoyancy is strong, the pressure gradient is negative, and the flow is entirely driven by buoyancy. External and structural buoyancy effects contribute to flow laminarization, leading to heat transfer deterioration. With increasing heat flux, Nu decreases more significantly, with a maximum reduction of 62.94%, and begins to recover after reaching its lowest point. Importantly, in the recovery stage, the structural buoyancy effect triggers turbulence recovery. The recovery of shear production of turbulent kinetic energy is later than that of buoyancy production and can only occur with a strong M−shaped velocity distortion. The FIK identity decomposition shows that the heat transfer deterioration is related to flow laminarization and inhomogeneous effects. Heat transfer recovery is purely due to the increase in turbulence components.

Synthesizing Sea Surface Temperature and Satellite Altimetry Observations Using Deep Learning Improves the Accuracy and Resolution of Gridded Sea Surface Height Anomalies

AbstractGridded sea surface height (SSH) maps estimated from satellite altimetry are widely used for estimating surface ocean geostrophic currents. Satellite altimeters observe SSH along one‐dimensional tracks widely spaced in space and time, making accurately reconstructing the two‐dimensional (2D) SSH field challenging. Traditionally, SSH is mapped using optimal interpolation (OI). However, OI artificially smooths the SSH field leading to high mapping errors in regions with rapidly‐evolving mesoscale features such as western boundary currents. Motivated by the dynamical relation between SSH and sea surface temperature (SST) and the notion that even the chaotic evolution of mesoscale ocean turbulence may contain repeating patterns, we outline a deep learning (DL) approach where a neural network is trained to reconstruct 2D SSH by synthesizing altimetry and SST observations. In the Gulf Stream Extension region, dominated by mesoscale variability, our DL method substantially improves the SSH reconstruction compared to existing methods. Our SSH map has 17% lower root‐mean‐square error and resolves spatial scales 30% smaller than OI compared against independent altimeter observations. Surface geostrophic currents calculated from our map are closer to surface drifter observations and appear qualitatively more realistic, with stronger currents, a clearer separation between the Gulf Stream and neighboring eddies, and the appearance of smaller coherent eddies missed by other methods. Our map yields significant re‐estimations of important dynamical quantities such as eddy kinetic energy, vorticity, and strain rate. Applying our DL method to produce a global SSH product may provide a more accurate and higher resolution product for studying mesoscale ocean turbulence.

Quantitative experimental research on vortex generation and self-maintenance mechanisms in turbulence

Turbulence is not completely random, but contains organized and multi-scale structures. Vortices have always been recognized as the most important coherent structure in turbulent flow, playing a significant role in the generation, evolution, and maintenance of turbulence. In the present work, the vortex formation and evolution process of a fully developed turbulent boundary layer in a rectangular channel flow is experimentally studied by moving-single frame and long exposure and moving-particle image velocimetry measurements. The Rortex integral (RI) method is proposed for quantitative statistics on the critical vortex core size as well as the accurate rotation strength during the evolution process. In this paper, the vortex regeneration and self-maintenance mechanisms in near-wall turbulent flow are experimentally revealed and quantified by the RI method, to give some revelations for the future research on the turbulence theory. On the one hand, three behaviors of the hairpin vortex regeneration are discovered to play a significant role in turbulence development: (A) hairpin regeneration induced by the interaction between hairpins and packets; (B) auto-generation of multiple hairpin vortex in one packet (secondary and tertiary hairpins); and (C) the merging of hairpin vortices in the packets. On the other hand, the circulation process, which contains a mass of young vortex growth with the parent self-decaying, is verified to sustain and promote the development of turbulence. In consequence, the self-sustaining turbulence theory based on mother–child hairpins generation mechanism is supported by the experimental results.

The evolution of fast turbulent deflagrations to detonations

We use advanced experimental techniques to explore turbulence-induced deflagration-to-detonation transition (tDDT) in hydrogen–air mixtures. We analyze the full sequence of turbulent flame evolution from fast deflagration-to-detonation using simultaneous direct measurements of pressure, turbulence, and flame, shock, and flow velocities. We show that fast turbulent flames that accelerate and develop shocks are characterized by turbulent flame speeds that exceed the Chapman–Jouguet deflagration speed in agreement with the tDDT theory and direct numerical simulation (DNS) results. Velocity and pressure evolutions are provided to detail the governing mechanisms that drive turbulent flame acceleration. Turbulent flame speeds and fluctuations are examined to reveal flow field characteristics of the tDDT process. This work contributes to the understanding of fundamental mechanisms responsible for spontaneous initiation of detonations by fast turbulent flames.

Production and transport of turbulent kinetic energy from premixed flames subjected to mean pressure gradients

The influence of mean favorable pressure gradients on the production and transport of turbulent kinetic energy is experimentally investigated in a premixed bluff-body combustor. The combustor wall geometry is modified into converging, straight, or diverging configurations to experimentally alter the mean pressure gradient in the reacting flow field. For each configuration, turbulent kinetic energy production and transport dynamics are characterized with high-speed particle image velocimetry and simultaneous CH* chemiluminescence imaging. For all cases, the premixed reaction increases the turbulent kinetic energy and integral length scales in the flow. However, increasing the magnitude of the mean favorable pressure gradient increases the turbulent kinetic energy produced by the flame. The source of increased turbulent fluctuations from reactants to products is first investigated with a steady flow energy analysis, and is accompanied with a Reynolds decomposed investigation of the kinetic energy in the flow. As the mean pressure gradient increases, the turbulent kinetic energy in the flow increases due to stronger magnitudes of flame-generated turbulence in the form of baroclinic torque. The evolution of the flame-generated turbulence is examined by decomposing the transport equation of turbulent kinetic energy. Increasing the mean favorable pressure gradient augments the largest magnitude transport terms, and the budget of turbulent kinetic energy is primarily driven by pressure gradient work and viscous dissipation. The results here differ from previous direct numerical simulation (DNS) studies, and should ultimately motivate additional research to aid the development of computational models which can better predict turbulent flame-flow dynamics in confined environments with mean pressure gradients.

Helios 2 observations of solar wind turbulence decay in the inner heliosphere

Aims. A linear scaling of the mixed third-order moment of the magnetohydrodynamic (MHD) fluctuations is used to estimate the energy transfer rate of the turbulent cascade in the expanding solar wind. Methods. In 1976, the Helios 2 spacecraft measured three samples of fast solar wind originating from the same coronal hole, at different distances from the Sun. Along with the adjacent slow solar wind streams, these intervals represent a unique database for studying the radial evolution of turbulence in samples of undisturbed solar wind. A set of direct numerical simulations of the MHD equations performed with the Lattice-Boltzmann code FLAME was also used for interpretation. Results. We show that the turbulence energy transfer rate decays approximately as a power law of the distance and that both the amplitude and decay law correspond to the observed radial temperature profile in the fast wind case. Results from MHD numerical simulations of decaying MHD turbulence show a similar trend for the total dissipation, suggesting an interpretation of the observed dynamics in terms of decaying turbulence and that multi-spacecraft studies of the solar wind radial evolution may help clarify the nature of the evolution of the turbulent fluctuations in the ecliptic solar wind.

Evolution of turbulence characteristics in the pre-precursor phase of tearing mode included disruption in the core of EAST

Avoiding the plasma instability, especially the disruption instability, is an important problem for the stable operation of tokamak. Large-scale instabilities driven by free energy evolve nonlinearly and lead to the disruption. The microscale turbulence is highly sensitive to the change of free energy. The paper show the electron-scale turbulence evolution in the pre-precursor phase of TMs included disruption with the laser coherent scattering system in EAST. In the pre-precursor phase of disruption, it is observed that the characteristics of turbulence (e.g. intensity, spatial correlation) have obviously changed for more than 30 ms. In addition, before TM () included major disruption, the spatial-correlation of turbulence in two regions ( = 0–0.4 and = 0.4–0.8) increase obviously, while opposite turbulence spatial-correlation evolution was observed before TM () included minor disruption. The warning time for disruption with microscale turbulence is competitive while 30 ms for ITER. According to the experimental results in EAST, it may provide a new experimental evidence for the method improvement of predicting disruption.

Numerical analysis of the hydrodynamic interaction between a propeller and trapezoidal rudder

The wake evolution of the propeller–rudder system is crucial to the noise performance of the vessel. The rudder operating in propeller wake impacts the distribution of turbulence in the propeller wake. Hence, the hydrodynamic interaction between the propeller and trapezoidal rudder is investigated. The asymmetric distribution of the pressure on the rudder is analyzed. The evolution of rudder tip vortex and propeller vortices in the downstream is discussed. The impact of trapezoidal rudder on the asymmetric evolution of propeller wake and turbulence is studied. The results suggest that the trapezoidal rudder induces asymmetric distributions of the pressure on the rudder. Pressure fluctuations in the rudder tip vortex can be strengthened by the interaction between the rudder tip vortex and propeller tip vortices. The turbulence in the downstream is enhanced by the interactions among propeller hub vortex, propeller tip vortices, rudder trail vortices and rudder tip vortex. Different to skew-symmetric distribution of turbulence induced by rectangular rudder, trapezoidal rudder leads to completely asymmetric evolution of propeller wake and then completely asymmetric distributions of turbulence. The impact of the rudder geometry on the wake evolution indicates that the turbulence in the propeller wake can be adjusted by optimizing rudder geometry.

Theory of magnetic turbulence and shock formation induced by a collisionless plasma instability

Magnetic fields are ubiquitous in universe, space, and laboratory plasmas. Especially, self-generated magnetic fields are important to know the mind of nature. The formation of Weibel-mediated collisionless shock is studied theoretically as a structure formation by the linear plasma wave growth, nonlinear saturation, and mode–mode coupling. Following a series of computer simulations and experimental studies of the physics, a simple model equation is proposed here to describe the time evolution of magnetic turbulence. Weibel instability is saturated by magnetic pressure, and thicker filaments continue to be generated by current coalescence (magnetic reconnection) mechanism. The model equation concludes the fact that the filament spacing increases linearly in time, and the magnetic energy power spectrum is given as Bk2 ∝ k−2. The time evolution of the turbulence is characterized with the cascade toward smaller k. Such inverse cascade is well-known in 2D hydrodynamic turbulence such as a typhoon or hurricane formation and is known to have Kolmogorov spectrum k−5/3. Although only a small difference in power, the physics of inverse cascades is very different as shown in the present paper. With use of Alfvén current limit condition, the criteria of collisionless shock formation are evaluated. The present theory is compared to corresponding experiments done with Omega and NIF lasers and a variety of PIC simulations. The theory is also applied to evaluate the strength of magnetic field near the shock front of the supernova remnant SN1006. The enhancement of magnetic field of about 25 μG is concluded in the present theory. Finally, a universality of the model equation is shown by applying the theory to the turbulent mixing due to Rayleigh–Taylor instability at the contact surface of two fluids in a gravitational or inertial force, which is very important in compressing plasma such as inertial confinement fusion by implosion. It is shown that the well-known evolution physics, mixing layer of the two fluids grows in proportion to (time)2, can be explained with the same model equation.

A Model for Gradual-phase Heating Driven by MHD Turbulence in Solar Flares

Coronal flare emission is commonly observed to decay on timescales longer than those predicted by impulsively driven, one-dimensional flare loop models. This discrepancy is most apparent during the gradual phase, where emission from these models decays over minutes, in contrast to the hour or more often observed. Magnetic reconnection is invoked as the energy source of a flare, but should deposit energy into a given loop within a matter of seconds. Models which supplement this impulsive energization with a long, persistent ad hoc heating have successfully reproduced long-duration emission, but without providing a clear physical justification. Here we propose a model for extended flare heating by the slow dissipation of turbulent Alfvén waves initiated during the retraction of newly reconnected flux tubes through a current sheet. Using one-dimensional simulations, we track the production and evolution of MHD wave turbulence trapped by reflection from high-density gradients in the transition region. Turbulent energy dissipates through nonlinear interaction between counter-propagating waves, modeled here using a phenomenological one-point closure model. Atmospheric Imaging Assembly EUV light curves synthesized from the simulation were able to reproduce emission decay on the order of tens of minutes. We find this simple model offers a possible mechanism for generating the extended heating demanded by observed coronal flare emissions self-consistently from reconnection-powered flare energy release.

Advanced turbulence and combustion modeling for the study of a swirl-assisted natural gas spark-ignition heavy-duty engine

Increasing demands on higher performance and lower fuel consumption and emissions have led the path for internal combustion engine development; this race is nowadays directly related to CO2 emissions reduction. To drive engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and calibration. The present work is focused on the improvement of the phenomenological turbulence model, originally conceived to describe turbulence evolution in tumble-promoting engines. The turbulence model is developed with reference to a SI heavy-duty CNG engine derived from a diesel engine. In this architecture, due to the flat cylinder head, turbulence is also generated by swirl and squish flow motions, in addition to tumble motion. The presented turbulence model is validated against 3D CFD results, demonstrating to properly predict turbulence and swirl/tumble evolution under two different operating conditions, without the need for any case-dependent tuning. The developed turbulence model is coupled to a phenomenological combustion model based on the fractal geometry theory applied to the flame front surface, where the turbulence is assumed to support flame propagation through an enhancement of the flame front area with respect to the laminar counterpart. The combustion model is validated against an extensive experimental dataset, composed of 25 operating points at different engine rotational speeds and loads. The numerical/experimental comparisons of global performance parameters are satisfactory, leading to maximum errors around ±2% for the BSFC, ±2° for the main combustion events, and ±1 bar for the in-cylinder peak pressure. Burn rate profiles are very well captured by the combustion model at changing operating conditions, not requiring any case-dependent tuning. The presented results demonstrate that the turbulence/combustion models could constitute a reliable virtual test facility, contributing to supporting and driving experimental activities.

Experimental study of the effect of a cavity on propagation behavior of premixed methane–air flame

In this study, experiments were performed in a closed duct with a cavity to reveal the effect of the cavity on the flame propagation behavior. A high-speed camera and three pressure sensors were used to measure the premixed flame evolution and pressure history, respectively. The results indicate that the cavity can prompt flame front propagation in the cavity region and at a certain distance downstream of the cavity via two mechanisms. The first mechanism involves an increase in the flame surface area owing to the vortex growth and turbulence evolution. In the second mechanism, the expansion flow from the delayed burning of the unburned gas within the vortex and cavity accelerates the flame front. The presence of the cavity causes the flame-tip velocity to fluctuate, and the frequency of rises and falls highly depends on the length scale of the cavity. For cases with a similarly scaled cavity depth (H/D), the maximum pressure (Pmax) increased approximately linearly with an increase in the scaled cavity length (L/D). When the L/D was kept constant, as the H/D increased, the Pmax increased for cases with L/D > 1, however, Pmax decreased for cases with L/D < 1. This trend resulted from the combined effect of the time required to attain the maximum pressure and the ratio of the volume to the surface area on the pressure reduction due to heat loss.